title: Seizure detection methods using a cascade architecture for real-time implantable devices.
abstract: Implantable high-accuracy, and low-power seizure detection is a challenge. In this paper, we propose a cascade architecture to combine different seizure detection algorithms to optimize power and accuracy of the overall seizure detection system. The proposed architecture consists of a cascade of two seizure detection stages. In the first-stage detector, a lightweight (low-power) algorithm is used to detect seizure candidates with the understanding that there will be a high number of false positives. In the second-stage detector-and only for the seizure candidates detected in the first detector-a high-accuracy algorithm is used to eliminate the false positives. We show that the proposed cascade architecture can reduce power consumption of seizure detection by 80% with high accuracy, offering a suitable option for real-time implantable seizure detectors.
authors.forename: Taehoon
authors.initials: T
authors.lastname: Kim
authors.forename: N Sertac
authors.initials: NS
authors.lastname: Artan
authors.forename: Ivan W
authors.initials: IW
authors.lastname: Selesnick
authors.forename: H Jonathan
authors.initials: HJ
authors.lastname: Chao
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003199:Computer Systems; D004567:Electrodes, Implanted; D006801:Humans; D012640:Seizures / Q000175:diagnosis*; D012815:Signal Processing, Computer-Assisted